Retrieving implicit positive meaning from negated statements

This paper introduces a model for capturing the meaning of negated statements by identifying the negated concepts and revealing the implicit positive meanings. A negated sentence may be represented logically in different ways depending on what is the scope and focus of negation. The novel approach introduced here identifies the focus of negation and thus eliminates erroneous interpretations. Furthermore, negation is incorporated into a framework for composing semantic relations, proposed previously, yielding a richer semantic representation of text, including hidden inferences. Annotations of negation focus were performed over PropBank, and learning features were identified. The experimental results show that the models introduced here obtain a weighted f-measure of 0.641 for predicting the focus of negation and 78 percent accuracy for incorporating negation into composition of semantic relations.

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